A method of this kind is known from SOURBELL, K.; KACHELRIESS, M.; KALENDER, W. A.: Reconstruction from truncated projections in CT using adaptive detruncation, Journal European Radiology, vol. 15, no. 5, May 2005, pages 1008-1014. The known method is particularly suitable for use in CT scanners with flat panel detectors (FPD). Laminar multi-line detectors of this kind are used in connection with C-arm computer tomography but also with CT scanners with a fixed gantry. However, the flat panel detectors are often not large enough to completely capture the lateral extension of the patient volume penetrated by radiation. Cropped projection images, which are also called truncated projection images, often occur therefore. In the reconstruction of object images, which is carried out by the evaluation unit, use of truncated projection images leads to pronounced artifacts and large density errors in the reconstructed object images. The truncated projection images are frequently extrapolated to suppress the errors in the object images caused by truncation. To carry out the extrapolation it is advantageous if the object region taken up by the object being examined is at least approximately known before carrying out the extrapolation. In the known method parameters of an elliptical envelope are determined by taking account of pre-defined consistency conditions of a large number of projection images for determining the object region. The optimization that is to be performed in the known method can require a plurality of iterations and therefore needs a relatively large amount of computing.
An extrapolation method is known from HSIEH, J.; CHAO, E.; THIBAULT, J.; GREKOWICZ, B.; HORST, A.; MCOLASH, S.; MYERS, T. J.: A novel reconstruction algorithm to extend the CT scan field-of-view, Med. Phys. 31 (9), September 2004, pages 2385-2391, in which, at the boundary of a truncated projection image, parameters of an equivalent water cylinder are determined and the truncated projection images are extrapolated using the equivalent water cylinder.
From ZELLERHOFF, M.; SCHOLZ, B.; RUHRNSCHOPF, E.-P.; BRUNNER, T.: Low contrast 3D reconstruction from C-arm data, Proceedings of SPIE, Medical Imaging 2005, vol. 5745, pages 646-655 a method for low-contrast representation in the three-dimensional reconstruction of tissue density distribution by means of C-arm computer tomography is also known. In this method a hybrid extrapolation is carried out in which, depending on the quality of the projection images at the cropped boundary, an extrapolation is performed with the aid of an equivalent water cylinder or by means of a Gaussian function. A method for beam hardening correction is also described in this document.
The cropped projection images can in principle also be processed using standard reconstruction algorithms. Standard reconstruction algorithms of the filtered back projection type are described for example in the publication FELDKAMP, L. A.; DAVIS, L. C.; KRESS, J. W.: Practical cone-beam algorithm, J. Opt. Soc. Amer. A, vol. 6, 1984, pages 612-619 and in the publication WIESENT, K.; BARTH, K.; NAVAB, N. et al.: Enhanced 3-D-Reconstruction Algorithm for C-Arm Systems Suitable for Interventional Procedures, IEEE Trans. Med. Imaging, vol. 19, no. 5, Mai 2000, pages 391-403.
Applying these standard reconstruction algorithms to truncated projection images leads to pronounced artifacts and large density errors in the reconstructed images, even if the cropped object regions lie outside of the reconstructed, examined region (ROI=region of interest). The correction algorithms mentioned in the introduction are therefore applied, with which the truncated data is extrapolated in the outer region where measuring data is missing.